Trends and transitions in labour market outcomes among adults

enrolled in the Free State province’s public sector antiretroviral treatment

(ART) programme

Frikkie Booysen, Department of Economics / CHSR&D, University of the Free State

Annual TIPS Forum: South Africa’s Economic Miracle – has the emperor lost his clothes?

Cape Sun, Cape Town

29-31 October 2008

Acknowledgement

• The financial support of CIDA, DCI, DfID, IDRC, JEAPP, USAID, AUSAID, UNDP, The World Bank’s Research Committee, and BNP Programme

• Patients in the ART programme who willingy sacrificed their time and energy to participate in this research, and frankly shared their views and experiences.

• The management and health care staff of the Free State Department of Health and of several local municipalities, who facilitated access to the study participants.

Background

• Adverse macro- and microeconomic impacts of HIV and AIDS are relatively well documented

• Access to ART is expanding rapidly in South Africa, Southern Africa and beyond, although coverage remains sub-optimal

… how can ART ameliorate these adverse economic impacts of HIV and AIDS?

Data: CP cohort study

– Sampling frame

• Eligible and certified ready to commence ART in 2004/05

• CD4<200 and/or WHO stage 4 + clinical assessment

– Randomly sampled

• 80/district proportional to treatment/non-treatment numbers

• Xhariep = 44 patients only, census

• Follow-up interviews at approximately 6- to 9-month intervals

• Replaced from original sampling frame if lost to follow-up

– Written, informed consent

• Nursing sister at assessment site + enumerator

– Sample size

• 6 survey rounds: 454 (n) individuals observed 1,844 times (N)

• 195 patients interviewed in all 6 survey rounds

• Attrition rate = 42.1%, mostly due to death, migration and refusal

Key outcomes

Labour market outcomes:

(a) Too ill to work

(b) Labour force participation

(c) Unemployment

(d) Absorption

(e) Discouraged

Treatment outcomes:

(a) Clinical markers

– CD4 count (copies/mm3)

– RNA level (copies/mL)

– CD4 > 350 and RNA < 500

(b) Self-reported illness

(c) Health-related quality of life

– EQ-5D

– EQ-VAS

(d) Self-reported side-effects

(e) Hospitalisation

TIM

E: T

RE

AT

ME

NT

CA

RE

ER

Key questions

(1) How do labour market outcomes and transitions in labour market outcomes vary by treatment

duration and/or treatment responses?

(2) Are treatment dynamics significant predictors of labour market outcomes and transitions in labour market outcomes?

Figure 2: Clinical outcomes, by treatment duration

0.1

.2.3

.4.5

.6.7

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1P

rob

abili

ty

-12 -6 0 6 12 18 24 30 36 42 48Treatment duration (months)

p_vl500 p_cd350p_vlcd4

Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

0.1

.2.3

.4.5

.6.7

.8.9

1P

rob

abili

ty

-12 -6 0 6 12 18 24 30 36 42 48Treatment duration (months)

Pr(vl500=1 assuming u_i=0) Pr(cd350=1 assuming u_i=0)Pr(vlcd4=1 assuming u_i=0)

(a) Pooled clinical data (b) Matched clinical data

Table 4: Subjective, self-reported outcomes, by treatment duration

Note: Standard errors reported in parentheses. Results for side effects only include patients on ARV treatment at the time. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27; N=130). Three asterisks denote differences that are statistically significant at the 1% level, while two asterisks denote differences that are statistically significant at the 5% level. Median values of all continuous variables also differ statistically significantly across treatment duration categories (p<0.001).

Feeling ill (%) 39.3 (4.3) 26.9 (3.2) 26.9 (2.3) 19.7 (1.8) 19.5 (2.1) 15.3 (10.4) ***

EQ-5D (0-1) 0.706 (0.034) 0.818 (0.020) 0.816 (0.014) 0.833 (0.012) 0.854 (0.013) 0.895 (0.013) *** 1,714

EQ-VAS (%) 63.1 (2.0) 66.5 (1.4) 67.7 (1.0) 70.0 (0.9) 71.4 (1.1) 74.9 (1.3) *** 1,710

Side effects (%) 50.0 (15.0) 52.6 (4.0) 31.4 (2.5) 10.0 (1.4) 8.1 (1.4) 6.6 (1.7) *** 1,541

Severity of side effects (%):

No side effects 50.0 47.7 68.5 89.9 92.8 93.9 *** 1,535

Non-disruptive side effects 8.3 4.0 2.3 0.7 0.0 0.0

Minor side effects 16.7 10.6 10.5 2.6 1.6 3.1

Severe side effects 25.0 37.8 18.7 6.8 5.6 3.1

Hospitalised (%) 11.2 (2.8) 8.9 (2.0) 13.2 (1.8) 6.5 (1.1) 6.8 (1.2) 9.0 (2.0) ** 1,705

Outcome

Treatment duration

Pre-ART 0-3 months 3-12 months 12-24 months 24-36 months >36 monthsSample

(n)

Figure 15a: Predicted probability of being too ill to work, by treatment outcomes and duration

Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

0.1

.2.3

.4.5

.6.7

.8.9

1P

rob

abili

ty

-12 -6 0 6 12 18 24 30 36 42 48Treatment duration (months)

RNA < 500 CD4 >= 350RNA < 500 and CD4 >= 350 Being too ill to work

Figure 15b: Predicted probability of participating in the labour force, by treatment outcomes and duration

0.1

.2.3

.4.5

.6.7

.8.9

1P

rob

abili

ty

-12 -6 0 6 12 18 24 30 36 42 48Treatment duration (months)

RNA < 500 CD4 >= 350RNA < 500 and CD4 >= 350 Participating in the labour force

Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

Figure 15c: Predicted probability of being absorped in the labour force, by treatment outcomes and duration

0.1

.2.3

.4.5

.6.7

.8.9

1P

rob

abili

ty

-12 -6 0 6 12 18 24 30 36 42 48Treatment duration (months)

RNA < 500 CD4 >= 350RNA < 500 and CD4 >= 350 Being absorped in the labour force

Note: Unadjusted predicted probabilities obtained from RE panel probit models. Includes all clinical markers for interviewed study participants. Data obtained from patient files. Results exclude those patients known to have interrupted their ARV treatment at some time or other during the study (n=27).

Table 8: Subjective, self-reported treatment outcomes as predictors of labour market outcomes

Note: Results are for random effects (RE) panel probit models including ONLY treatment dynamics as explanatory variable. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type eydx. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

Self-reported illness t1 - t : [Comparison group = treatment t * not ill in either period]

Treatment t * Fell ill t1 - t 1.337 *** -0.480 *** -0.976 ** Treatment t * Not ill any longer t1 - t 0.871 *** -0.437 *** 0.015 Treatment t * Remained ill t1 - t 1.688 *** -0.739 *** -1.366 **

Health-related quality of life (EQ-VAS) t1 - t (x10): Baseline EQ-VAS -0.019 *** 0.010 *** 0.015 Treatment t * EQ-VAS t 0.178 * -0.051 0.178 Treatment t * EQ-VAS t1 - t -0.299 *** 0.075 0.191

Health-related quality of life (EQ-5D) t1 - t (x10): Baseline EQ-5D -1.643 *** 0.811 *** 2.013 * Treatment t * EQ-5D t 0.048 -0.095 * 0.156 Treatment t * EQ-5D t1 - t -0.195 *** 0.118 *** 0.015

Presence of self-reported side effects t1 - t : [Comparison group = treatment t * still no side effects]

Treatment t * Continued side effects 1.307 *** -0.464 *** -0.864

Presence and severity of self-reported side effects t1 - t : [Comparison group = treatment t * still no side effects]

Treatment t * Persistent, severe side effects 1.725 *** -0.607 *** -1.140

Hospitalisation t1 - t : [Comparison group = treatment t * not hospitalised in either period]

Treatment t * Recently hospitalised 0.904 *** -0.425 *** -1.302 **

Absorped in the labour market

Too ill to workLabour force participation

Table 9: Treatment duration and/or subjective, self-reported outcomes as predictors of labour market outcomes

Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type dydx. Adjusted for gender, age, race, education, dwelling, marital status, dependency ratio, employment status at first HIV-positive test, access to disability grant, breadwinner status, access to inter-household employment networks, self-reported stigmatisation, district, follow-up duration, and month and year of interview. Three asterisks denote differences statistically significant at the 1% level, two and one asterisk significance at 5% and 10% levels respectively.

Treatment duration t : [Comparison group = pre-ART]

0-3 months -0.883 -5.201 -4.580 3-12 months -1.675 *** 1.666 *** 0.426 12-24 months -1.813 *** 1.559 *** 0.590 24-36 months -1.625 *** 1.793 *** 0.793 >36 months -1.206 * 1.476 ** 0.706

Self-reported illness t1 - t : [Comparison group = treatment t * not ill in either period]

Not on ARV treatment t 1.054 *** -0.767 ** 0.184 Treatment t * Fell ill t1 - t 0.957 *** -0.633 *** -0.623 * Treatment t * Not ill any longer t1 - t 0.750 *** -0.785 *** -0.118 Treatment t * Remained ill t1 - t 1.019 *** -0.926 *** -0.267

Health-related quality of life (EQ-VAS) t1 - t (x10): Baseline EQ-VAS -0.008 * 0.009 * 0.004 Treatment t * EQ-VAS t1 - t -0.263 *** 0.086 0.154

Health-related quality of life (EQ-5D) t1 - t (x10): Treatment t * EQ-5D t1 - t -0.202 *** 0.234 *** 0.037

Presence of self-reported side effects t1 - t : [Comparison group = treatment t * still no side effects]

Treatment t * Continued side effects 1.010 *** -0.806 ** -0.409

Presence and severity of self-reported side effects t1 - t : [Comparison group = treatment t * still no side effects]

Treatment t * Persistent, severe side effects 1.279 *** -0.750 * 0.277

Being too ill to workParticipating in the

labour forceBeing absorped in the

labour force

Tables 10-12: Other predictors of labour market outcomes

Female -0.420 ** to -0.592 ***Age 0.166 * to 0.234 *** 0.253 ** to 0.322 **

Age2 -0.002 *** to -0.003 *** -0.003 *** to -0.004 ***

Education: [Comparison group = no education]

Grade 12 1.013 ** to 1.454 *** 1.145 to 1.472 ** Diploma/degree 3.167 *** to 3.732 *** 2.621 *** to 2.940 ***

Dwelling type t : [Comparison group = formal dwelling]

Traditional dwelling 0.306 to 0.513 ** -0.401 ** to -0.560 *** -0.540 ** to -0.898 ***

Grant recipient status t1 - t : [Comparison group = received a grant in neither period] New grant recipient t 0.478 ** to 0.744 *** -0.774 *** to -0.926 *** -1.503 *** to -1.589 *** Not receiving grant any longer t1 - t 0.617 ** to 0.954 *** Grant recipient in both periods t1 - t 0.634 *** to 1.022 *** -0.658 *** to -0.921 *** -1.292 *** to -1.619 ***

Breadwinner status t1 - t : [Comparison group = not main breadwinner in either period] Became main breadwinner t -0.445 ** to -0.637 ** 0.561 ** to 0.686 ** 0.742 ** to 1.127 *** Main breadwinner in both periods t1 - t 0.446 ** to 0.551 ** 1.179 *** to 1.459 ***

Access to employment network t1 - t : [Comparison group = no other employed person in hhold in either period] Household recently gained an employed person t 0.442 * to 0.525 ** Household does not include employed person any longer t1 - t -0.368 to -0.621 ** Household included employed person in both periods t1 - t 0.640 * to 0.965 ***

Employed when first tested HIV-positive 1.096 *** to 1.374 ***

Being too ill to work Participating in the labour force Being absorped in the labour force

Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.001). Results are reported as marginal effects of type dydx. Adjusted for treatment duration/outcomes, gender, age, race, education, dwelling, marital status, dependency ratio, employment status at first HIV-positive test, access to disability grant, breadwinner status, access to inter-household employment networks, self-reported stigmatisation, district, follow-up duration, and month and year of interview. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

Table 13: Treatment duration and outcomes as predictors of transitions in select labour market outcomes

Self-reported illness t1 - t : [Comparison group = treatment t * not ill in either period]

Treatment t * Fell ill t1 - t -1.029 *** 1.317 *** -1.062 *** 2.342 ** -1.117 ** -0.746 * Treatment t * Not ill any longer t1 - t -0.436 ** 0.355 -0.539 ** -0.950 0.130 -1.998 *** Treatment t * Remained ill t1 - t -0.803 *** 1.416 *** -0.848 *** 3.111 ** -0.464 -0.677

Health-related quality of life (EQ-VAS) t1 - t (x10): Baseline EQ-VAS 0.004 -0.018 ** 0.006 -0.021 ** -0.001 0.000 Treatment t * EQ-VAS t -0.111 0.220 -0.331 *** 0.046 -0.169 -0.201 Treatment t * EQ-VAS2

t 0.018 ** -0.038 ** 0.040 *** -0.024 0.030 ** 0.031 Treatment t * EQ-VAS t1 - t 0.128 -0.413 ** 0.365 *** 0.045 0.326 ** 0.044 Treatment t * EQ-VAS2 t1 - t -0.001 -0.012 -0.033 -0.099 ** -0.049 -0.032

Health-related quality of life (EQ-5D) t1 - t (x10): Baseline EQ-5D 0.423 -1.052 * 0.933 ** 0.189 Treatment t * EQ-5D t -0.081 0.187 -0.180 * -0.002 Treatment t * EQ-5D2

t 0.014 * -0.026 * 0.024 ** -0.016 Treatment t * EQ-5D t1 - t 0.177 *** -0.110 0.290 *** -0.116 Treatment t * EQ-5D2 t1 - t -0.013 * -0.025 -0.024 ** -0.009

Not any longer too ill to work

Became too ill to work

Now participating in the labour force

Not participating in the labour force

any longer

Newly absorped in the labour force

Not absorped in the labour force

any longer

Note: Results are for pooled or random effects (RE) panel probit models including ONLY treatment dynamics as explanatory variable. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type eydx. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

Tables 14-16: Treatment duration and outcomes as predictors of transitions in select labour market outcomes

Self-reported illness t1 - t :

[Comparison = treatment t * not ill either period]

Not on ARV treatment t -0.700 ** -1.052 *** 0.769 ** 0.801 ** 0.817 * 1.105 ** Treatment t * Fell ill t1 - t -1.495 *** -1.370 *** 0.658 *** 0.637 *** -1.119 *** -0.942 *** -0.860 ** -0.720 * Treatment t * Not ill any longer t1 - t -0.701 *** -0.915 *** -0.508 ** -0.588 ** -1.003 ** -0.888 * Treatment t * Remained ill t1 - t -1.245 *** -1.419 *** 0.879 *** 0.773 ** -0.827 *** -0.755 ** 0.984 ** 0.596

Health-related quality of life (EQ-VAS) t1 - t (x10):

Baseline EQ-VAS -0.014 *** -0.013 * Treatment t * EQ-VAS t -0.260 *** -0.231 ** -0.216 ** -0.254 ** Treatment t * EQ-VAS2

t 0.031 *** 0.030 *** 0.027 *** 0.031 *** Treatment t * EQ-VAS t1 - t -0.197 ** -0.156 * 0.280 *** 0.311 *** 0.231 ** 0.282 *** Treatment t * EQ-VAS2 t1 - t -0.039 * -0.046 **

Health-related quality of life (EQ-5D) t1 - t (x10):

Treatment t * EQ-5D t1 - t 0.209 *** 0.257 *** 0.196 ** 0.246 *** Treatment t * EQ-5D2 t1 - t -0.016 * -0.021 ** -0.014 * -0.018 **

Illness/disability Participation Absorption

Not any longer too ill to work

Became too ill to workNow participating in

the labour force

Not participating in the labour force any

longer

Newly absorped in the labour force

Not absorped in the labour force any

longer

Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type dydx. Adjusted for gender, age, education, dwelling, marital status, dependency ratio, access to disability grant, breadwinner status, access to inter-household employment network, self-reported stigmatisation, district, follow-up duration, and survey round. Results for 2nd model also adjusted for employment status at first HIV-positive test, which was observed in survey rounds 5/6 only. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

Tables 14-16: Other predictors of transitions in select labour market outcomes

Note: Results are for pooled or random effects (RE) panel probit models. All models are statistically significant in respect of overall fit (p<0.10). Results are reported as marginal effects of type dydx. Adjusted for gender, age, education, dwelling, marital status, dependency ratio, access to disability grant, breadwinner status, access to inter-household employment network, self-reported stigmatisation, district, follow-up duration, and survey round. Results for 2nd model also adjusted for employment status at first HIV-positive test, which was observed in survey rounds 5/6 only. Three asterisks denote differences that are statistically significant at the 1% level, while two and one asterisk denote significance at the 5% and 10% levels respectively.

Age 0.158 to -0.248 ** 0.025 to 0.123 *** 0.040 to 0.156 *** 0.036 to 0.129 ** 0.101 to 0.204 ***

Age2 0.001 to 0.002 * -0.001 to -0.001 * -0.001 to -0.002 *** -0.001 to -0.001 ** -0.001 to 0.002 ***

Education:

[Comparison group = no education]

Primary education 5.188 *** to 5.598 *** Some secondary education 5.449 *** to 5.711 *** Grade 12/diploma/degree -0.952 to -1.647 *** 5.287 *** to 5.706 ***

Dwelling type t :

[Comparison group = formal dwelling]

Informal dwelling 0.866 * to 1.508 ** 0.451 to 0.951 * Traditional dwelling -0.400 * to -0.515 *** 0.282 to 0.495 *

Received disability grant 0.411 ** to 0.521 *** 0.139 to 0.549 *** -0.382 ** to -0.474 *** -0.639 *** to -0.958 ***

Main breadwinner 0.662 *** to 0.887 ***

Access to employment network 0.240 to 0.387 **

Employed when first tested HIV-positive -0.475 ** to -0.585 *** 0.451 ** to 0.571 *** 0.561 *** to 0.591 ***

Absorption

Not any longer too ill to work

Became too ill to workNow participating in the

labour forceNot participating in the labour force any longer

Newly absorped in the labour force

Not absorped in the labour force any longer

Illness/disability Participation

Limitations

• Observations of clinical (dates of facility visits) and labour market outcomes (interview dates) are not synchronised

• Limited information regarding actual timing and/or duration of the observed labour market outcomes

• Counterfactual unclear in absence of comparative samples of HIV-negative and/or HIV-positive persons not on ART

• Potential attrition and selection bias in socio-demographics and key clinical and labour market outcomes

• Poor overall fit of regression models for transitions in labour market outcomes: poor specification and/or unobservables?

• ‘Over’-adjusting for time: treatment effects may ‘dissolve’ or ‘vanish’ if adjusting for temporal dimensions of survey data?

• Endogeneity of select explanatory variables

Key findings

• Clinical outcomes and self-reported illness and/or health-related quality of life are strongly correlated

• Initial increase in labour force participation early in treatment career, accompanied by decline in participation later in treatment career

• ART patients worse off compared to representative LFS samples, with exception of (illness/disability and) labour force participation

• Improvements in self-reported health rather than clinical markers explain labour market outcomes and/or transitions

• Links to labour market and being employed at first HIV+ test significantly associated with labour market outcomes

• Access to social grants remain key determinant of observed labour market outcomes: key protection or predicament?

• Significantly ‘worse’ outcomes in informal settlements and rural areas (for persons residing in traditional dwellings‘’)

Conclusions

• Sustainable, effective treatment key for improved labour market outcomes

, BUT ART is not a “magic bullet” for problems of poverty, development and underdevelopment?

• Direct benefits for the economy relative limited among this group of ART clients (i.e. public sectors users), among which employment is low and often informal, especially in informal settlements and rural areas

• Important therefore to estimate the indirect benefits or externalities of provision of treatment (e.g. time allocation, schooling, health care seeking behaviour) these social and economic spin-offs represents the focus of ongoing longitudinal research in this area